Southern Apuan Alps (Italy) are strongly prone to rainfall-induced landslides. A first attempt to calculate rainfall thresholds was made in 2006 using non-statistical and repeatable methods for the 1975-2002 period. This research aims to update, validate, and compare the results of that attempt through different statistical approaches. Furthermore, a new dataset of rainfall and landslides from 2008 to 2016 was collected and analyzed by reconstructing the rainfall events via an automatic procedure. To obtain the rainfall thresholds in terms of the duration-intensity relationship, we applied three different statistical methods for the first time in this area: logistic regression (LR), quantile regression (QR), and Least-squares linear fit (LSQ). The updated rainfall thresholds, ob-tained through statistical methods and related to the 1975-2002 dataset, resulted in little difference from the ones obtained with not-statistical methods and have similar efficiency values among themselves. The best one is provided by the LR, with a landslide probability of 0.55 (efficiency of 89.8%). The new rainfall thresholds, calculated by applying the three statistical methods on the 2008-2016 dataset, are similar to the 1975-2002 ones, except for the LR threshold, which exhibits a higher slope. This result confirms the validity of the thresholds obtained with the old database.
An Update on Rainfall Thresholds for Rainfall-Induced Landslides in the Southern Apuan Alps (Tuscany, Italy) Using Different Statistical Methods
Roberto Giannecchini
Primo
;Michele BarsantiUltimo
2024-01-01
Abstract
Southern Apuan Alps (Italy) are strongly prone to rainfall-induced landslides. A first attempt to calculate rainfall thresholds was made in 2006 using non-statistical and repeatable methods for the 1975-2002 period. This research aims to update, validate, and compare the results of that attempt through different statistical approaches. Furthermore, a new dataset of rainfall and landslides from 2008 to 2016 was collected and analyzed by reconstructing the rainfall events via an automatic procedure. To obtain the rainfall thresholds in terms of the duration-intensity relationship, we applied three different statistical methods for the first time in this area: logistic regression (LR), quantile regression (QR), and Least-squares linear fit (LSQ). The updated rainfall thresholds, ob-tained through statistical methods and related to the 1975-2002 dataset, resulted in little difference from the ones obtained with not-statistical methods and have similar efficiency values among themselves. The best one is provided by the LR, with a landslide probability of 0.55 (efficiency of 89.8%). The new rainfall thresholds, calculated by applying the three statistical methods on the 2008-2016 dataset, are similar to the 1975-2002 ones, except for the LR threshold, which exhibits a higher slope. This result confirms the validity of the thresholds obtained with the old database.File | Dimensione | Formato | |
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